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Full Scale Performance: Single Process, Sharrow Off, Explicit Chunking #20

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aletzdy opened this issue Jun 6, 2024 · 1 comment
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@aletzdy
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aletzdy commented Jun 6, 2024

This is the issue to report on memory usage and runtime performance...

data_dir: "data-full" full scale skims (24333 MAZs)
households_sample_size: 0 (full scale 100% sample of households)
sharrow: "false"
multiprocess: false single process
chunk_training_mode: explicit

@aletzdy
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aletzdy commented Jun 6, 2024

Run with full sample, sharrow on, and single process (1 TB memory, Intel Xeon Gold 6342 @ 2.8GHz machine).

Runtime is 1428.2 mins (compared to 1,433.1 mins for a similar run with NO chunking)
Chunking is set to explicit in settings_mp.yaml, and explicit chunking is enabled for a number of models whose memory usage was higher than 300Gb in a previous sharrow run with same specs but with NO chunking. These models are:

compute_accessbility
mandatory_tour_scheduling
non-mandatory_tour_scheduling
trip_destination

For these models, the argument explicit_chunk was set to 0.5 in each respective model's yaml file, indicating the need for 2 (=1/0.5) chunks. Further chunks may be added in other tests and as required.

timing_log.csv
activitysim.log
memory_profile.csv

image

Below is the run without chunking:

image <style> </style>
event full_rss_gb_chunking full_rss_gb_No_chunking Difference % Diff accounting for skims
preload_injectables 2.167452 2.527322 -0.35987 NA
initialize_proto_population 173.9227 174.1077 -0.18509 NA
compute_disaggregate_accessibility 206.3356 201.5561 4.779454 17.4%
initialize_landuse 180.1346 175.3758 4.75886 375.3%
initialize_households 198.2141 193.3762 4.837839 25.1%
compute_accessibility 276.3907 367.4861 -91.0954 -47.1%
av_ownership 184.3127 180.3675 3.945181 63.0%
auto_ownership_simulate 202.3356 197.699 4.636545 19.7%
work_from_home 193.0878 192.2186 0.869179 4.8%
external_worker_identification 194.0765 192.6287 1.447735 7.8%
external_workplace_location 194.758 192.3864 2.371576 13.0%
school_location 292.9196 289.0295 3.890065 3.4%
workplace_location 402.6434 397.1514 5.49206 2.5%
transit_pass_subsidy 194.9363 192.3512 2.585076 14.2%
transit_pass_ownership 194.0668 193.3555 0.711307 3.7%
vehicle_type_choice 270.9691 265.4805 5.488607 6.0%
adjust_auto_operating_cost 183.9534 178.5603 5.393015 121.1%
transponder_ownership 188.1608 182.8532 5.30756 60.7%
free_parking 194.9765 193.1514 1.825108 9.6%
telecommute_frequency 195.4649 192.9583 2.506637 13.3%
cdap_simulate 195.6484 193.3964 2.252005 11.7%
mandatory_tour_frequency 195.0767 194.2196 0.857059 4.3%
mandatory_tour_scheduling 330.5758 453.69 -123.114 -44.0%
school_escorting 214.1988 208.6679 5.530911 16.0%
joint_tour_frequency_composition 205.0339 201.3234 3.710493 13.6%
external_joint_tour_identification 201.6065 201.7927 -0.18614 -0.7%
joint_tour_participation 199.2767 194.9526 4.324151 20.7%
joint_tour_destination 207.107 202.9316 4.175458 14.5%
external_joint_tour_destination 196.1608 191.8689 4.291928 24.2%
joint_tour_scheduling 212.2434 212.0547 0.188678 0.5%
non_mandatory_tour_frequency 238.0545 233.7386 4.315931 7.2%
external_non_mandatory_identification 208.9876 207.5797 1.407865 4.2%
non_mandatory_tour_destination 383.1723 379.6374 3.534909 1.7%
external_non_mandatory_destination 197.0708 192.72 4.350751 23.4%
non_mandatory_tour_scheduling 227.4625 275.858 -48.3955 -47.6%
vehicle_allocation 218.2018 217.5814 0.620433 1.4%
tour_mode_choice_simulate 217.6302 212.2314 5.398741 14.2%
atwork_subtour_frequency 196.0487 190.7215 5.327159 32.1%
atwork_subtour_destination 295.5799 290.2229 5.357048 4.6%
atwork_subtour_scheduling 211.7981 206.3961 5.401965 16.7%
atwork_subtour_mode_choice 198.8897 193.8696 5.020123 25.4%
stop_frequency 222.6066 217.8433 4.7633 10.9%
trip_purpose 199.3885 195.7768 3.611701 16.7%
trip_destination 426.6972 536.408 -109.711 -30.3%
trip_purpose_and_destination 206.8114 201.6604 5.150953 18.7%
trip_scheduling 208.1987 204.3938 3.804885 12.6%
trip_mode_choice 224.9043 219.6366 5.267706 11.6%
parking_location 292.0136 303.9549 -11.9413 -9.2%
write_data_dictionary 210.6467 207.9639 2.682831 7.9%
track_skim_usage 204.6225 202.1674 2.455048 8.7%
write_trip_matrices 298.8238 296.5611 2.262761 1.8%
write_tables 257.3621 255.2239 2.138206 2.6%
finalizing 230.174 228.311 1.862975 3.4%

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